Introduction: Access to time-critical stroke therapy, particularly remotely, is limited by the distance to travel to stationary brain scanners. A lightweight (<15kg), backpack sized ‘First Responder’ brain scanner has been developed utilising non-ionising electromagnetic (ultra-high frequency radio) signals for urgent stroke diagnosis. A brain scan is completed in minutes for the purposes of stroke classification and localisation, which is then transmitted to a telehealth connected neurologist. The study aims to evaluate the implementation of the First Responder brain scanner into the aeromedical retrieval workflow. Methods: This workflow implementation study will enrol aeromedical retrieval patients over an 8 week period (approximately 30 participants). Lower acuity aeromedical retrievals (e.g. non-emergency medical condition or interhospital transfer) will be initially targeted for enrolment to ensure patient safety is prioritised. Brain scans with the First Responder brain scanner will be completed in the field at the location of retrieval. Workflow metrics will be evaluated including time-on-scene, scan procedure duration, and telehealth network connectivity. The device’s safety, reliability, scan quality and usability will also be evaluated, as well as participant experience. Results: Preliminary results have demonstrated that the First Responder device withstood the rigors of aeromedical flight and successfully completed 3 healthy volunteer scans in rural South Australia. Scan sites included a remote community (Marree) and regional centre (Port Augusta), spanning distances of approximately 245-970km (45-105 minute flight) from Adelaide air base. Successful scans of healthy volunteers allowed advancement to patients subject to aeromedical retrieval. The aeromedical clinical study is now underway, enrolling patients across rural South Australia. Full implementation data will be presented. Conclusions: This study represents the world-first aeromedical integration of a miniaturised brain scanner capable of real-time, rural and remote stroke diagnosis. The device demonstrated operational resilience, scan fidelity, and workflow compatibility under retrieval conditions. Pending clinical validation, this model offers a pathway to reshape stroke systems of care: decentralising diagnosis, accelerating triage and potential treatment, and closing stroke care equity gaps for remote populations.
Santos et al. (Thu,) studied this question.